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hoyyeva/anthropic-local-image-path
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Originally created by @FairyTail2000 on GitHub (Mar 19, 2024).
Original GitHub issue: https://github.com/ollama/ollama/issues/3243
Originally assigned to: @dhiltgen on GitHub.
What is the issue?
Steam Deck GPU not supported (apperantly)
Logs:
What did you expect to see?
Steam Deck GPU being supported
Steps to reproduce
Start the official rocm docker container on the steam deck
docker run --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm
Are there any recent changes that introduced the issue?
No response
OS
Linux
Architecture
amd64
Platform
Docker
Ollama version
0.1.29
GPU
AMD
GPU info
ROCk module is loaded
HSA System Attributes
Runtime Version: 1.1
System Timestamp Freq.: 1000.000000MHz
Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model: LARGE
System Endianness: LITTLE
==========
HSA Agents
Agent 1
Name: AMD Custom APU 0932
Uuid: CPU-XX
Marketing Name: AMD Custom APU 0932
Vendor Name: CPU
Feature: None specified
Profile: FULL_PROFILE
Float Round Mode: NEAR
Max Queue Number: 0(0x0)
Queue Min Size: 0(0x0)
Queue Max Size: 0(0x0)
Queue Type: MULTI
Node: 0
Device Type: CPU
Cache Info:
L1: 32768(0x8000) KB
Chip ID: 0(0x0)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 2800
BDFID: 0
Internal Node ID: 0
Compute Unit: 8
SIMDs per CU: 0
Shader Engines: 0
Shader Arrs. per Eng.: 0
WatchPts on Addr. Ranges:1
Features: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: FINE GRAINED
Size: 12073356(0xb8398c) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 2
Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED
Size: 12073356(0xb8398c) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 3
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 12073356(0xb8398c) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
ISA Info:
Agent 2
Name: gfx1033
Uuid: GPU-XX
Marketing Name: AMD Radeon Graphics
Vendor Name: AMD
Feature: KERNEL_DISPATCH
Profile: BASE_PROFILE
Float Round Mode: NEAR
Max Queue Number: 128(0x80)
Queue Min Size: 64(0x40)
Queue Max Size: 131072(0x20000)
Queue Type: MULTI
Node: 1
Device Type: GPU
Cache Info:
L1: 16(0x10) KB
L2: 1024(0x400) KB
Chip ID: 5173(0x1435)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 0
BDFID: 1024
Internal Node ID: 1
Compute Unit: 8
SIMDs per CU: 2
Shader Engines: 1
Shader Arrs. per Eng.: 1
WatchPts on Addr. Ranges:4
Features: KERNEL_DISPATCH
Fast F16 Operation: TRUE
Wavefront Size: 32(0x20)
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Max Waves Per CU: 32(0x20)
Max Work-item Per CU: 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
Max fbarriers/Workgrp: 32
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 4194304(0x400000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 2
Segment: GROUP
Size: 64(0x40) KB
Allocatable: FALSE
Alloc Granule: 0KB
Alloc Alignment: 0KB
Accessible by all: FALSE
ISA Info:
ISA 1
Name: amdgcn-amd-amdhsa--gfx1033
Machine Models: HSA_MACHINE_MODEL_LARGE
Profiles: HSA_PROFILE_BASE
Default Rounding Mode: NEAR
Default Rounding Mode: NEAR
Fast f16: TRUE
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
FBarrier Max Size: 32
*** Done ***
CPU
AMD
Other software
No response
@FairyTail2000 commented on GitHub (Mar 19, 2024):
Further testing shows that forcing gfx1030 works and is compatible. The docker line for this is:
docker run --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 -e "HSA_OVERRIDE_GFX_VERSION=gfx1030" --name ollama ollama/ollama:rocm
It might be worth to stick a note onto the docker image page explaining this. So that future users don't need to find this issue to get it working
@dhiltgen commented on GitHub (Mar 20, 2024):
Glad to hear the override worked for this GPU.
@FairyTail2000 commented on GitHub (Mar 26, 2024):
@dhiltgen override no longer works on the newest beta version of steam os.
@5310 commented on GitHub (Mar 26, 2024):
I can't get the image to run on my still on stable 3.5.7 SteamOS either, with the override ofc.
Did you also used to get the
/sys/module/amdgpu/versionmissing back when it did work, @FairyTail2000?Edit: Or could you tell me what the exact version of the image worked for you, so I can try that instead of latest?
@FairyTail2000 commented on GitHub (Mar 26, 2024):
@5310 Yes I did get the missing amdgpu version error.
The exact image is sha256:9b14e2877bf00cd2a24f1ee8e92512f4d1164f7c4132fffe7b55ebc7aa79d7f0. It should be the latest. I haven't changed the image since then
@5310 commented on GitHub (Mar 26, 2024):
Thanks a lot! Let's see what I'm doing wrong then, I'm also on that image... 🤔
@FairyTail2000 commented on GitHub (Apr 4, 2024):
@dhiltgen the newest rocm docker image just hangs doing nothing. Not even the cpu runner seems to be starting
https://hub.docker.com/layers/ollama/ollama/rocm/images/sha256-7986e8c813e478064978e0a17cebb93af58f27f05ca6ee613c0d3b0850048c93?context=explore
@dhiltgen commented on GitHub (Apr 23, 2024):
@FairyTail2000 can you share a log of the container with debug enabled so we can see more details on the hang?
docker run ... -e OLLAMA_DEBUG=1 ...@FairyTail2000 commented on GitHub (Apr 24, 2024):
Thanks for the response, it seems like I just misinterpreted the output and it was just waiting for requests. However it still uses the cpu, is there anyway I can add additional drivers for gpu's at runtime? Or is it more complex to add a new driver?
@dhiltgen commented on GitHub (Apr 28, 2024):
@FairyTail2000 are you setting the override variable as mentioned earlier in this issue? If not, that will explain why it is running on CPU. If you are setting it and it's still not working on the GPU, can you share your server log so we can investigate?
@FairyTail2000 commented on GitHub (Apr 29, 2024):
Yes I do set the enviroment variable. Here is the command line and debug logs (after loading llama3:instruct remotely)
(deck@steamdeck ~)$ docker run --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 -e "HSA_OVERRIDE_GFX_VERSION=gfx1030" -e "OLLAMA_DEBUG=1" --name ollama ollama/ollama:0.1.30-rc4-rocm
@Talleyrand-34 commented on GitHub (Jun 5, 2024):
Sorry, but after reading this i don't understand, ollama has steamdeck support?
@FairyTail2000 commented on GitHub (Jun 6, 2024):
Thanks for your responds. But at least for my steam deck, it reports the driver as incompatible and with the override, the gpu initilization will fail
If yours behaves differently, please share your configuration so I can replicate it
@dhiltgen commented on GitHub (Jun 6, 2024):
My suspicion is the bundled ROCm library we're including is somehow incompatible with the system. Building from source might be a viable workaround until we can get this resolved.
Unable to init GPU: invalid device ordinal@sammcj commented on GitHub (Jun 7, 2024):
Might be related - I'm using nvidia GPUs (Ryzen 7600 CPU/APU though) but I noticed recently Ollama is spamming the logs with AMD GPU errors similar to above even when I'm not passing any AMD GPU through to the container.
Note that this occurs even when building Ollama from source.
@xyproto commented on GitHub (Jun 9, 2024):
Does it work now on the Steam Deck if you:
passwdto create a password for the deck user.sudo btrfs property set -ts / ro false.sudo pacman-key --init.sudo pacman-key --populate archlinux.sudo pacman -Sy.sudo pacman -S ollama-rocm.sudo systemctl restart ollama.ollama run tinyllama "Write a haiku about 7 llamas"?
@FairyTail2000 commented on GitHub (Jun 10, 2024):
I do not have enough space on my system partition for this to check, but since I use docker for my work with ollama, I would really like a solution for that
@sebastianlutter commented on GitHub (Jun 11, 2024):
@xyproto I don't have the
ollama-rocmavailable with pacman after following your steps:Then:
Don't know why I don't see the package:
@xyproto commented on GitHub (Jun 11, 2024):
@sebastianlutter Ah, it will probably be available in a later release of SteamOS, then. In the mean time, enabling pacman mirrors and repositories in /etc and then installing the package is probably possible. Or installing the binary package directly with pacman -U. I'll have to test this myself before having a definite answer.
@Talleyrand-34 commented on GitHub (Jun 11, 2024):
I tried to install ollama-rocm from aur but needs pacman 6.1 and steam only delivers pacman 6.0.
Also important thing
@Talleyrand-34 commented on GitHub (Jun 11, 2024):
Here is ollama new installed:
Is it the version?
Override gpu driver 1030 and debug log
Rocminfo
@Talleyrand-34 commented on GitHub (Jun 11, 2024):
Aditionally I would recommend an special method to install ollama on steam deck / modify installation path because with an update everything outside of /home is wiped.
@sebastianlutter commented on GitHub (Jun 11, 2024):
I got it working with docker like this on my steam deck:
GPU support seems to work:
Steam version:
GPU:
@5310 commented on GitHub (Jun 12, 2024):
Still looks like it's running of of CPU though. At least it did on my Deck after I tried to run that version just now—was checking the system resource monitor and only the CPU ramps up. Same error message.
Edit: It seems while I still don't have a
/sys/module/amdgpu/versionfile on the Deck, I do have a/sys/module/amdgpu/srcversionfile, containingD97512588BEE2F480E82473@Talleyrand-34 commented on GitHub (Jun 12, 2024):
I also get this, but if you read the characteristics of the gpu you notice that it is not the specs of the gpu. Moreover "ollama serve" fails to start due to this gpu does not exists
@FairyTail2000 commented on GitHub (Jun 12, 2024):
I tried to replicate the logs in my initial report. This is no longer possible, it now just crashes with the error, core dumped.
https://gist.github.com/FairyTail2000/c14a26441afc7a944b032b5da403fb7c
https://gist.github.com/FairyTail2000/e4e643aefbf94fdd0d14057965797008
Those are the full debug logs including the command line used. The initialization of the gpu now fails repeatedly. It no longer falls back to cpu, when trying to load a model into the gpu. It crashes and reports the crash to the ollama client
@sebastianlutter commented on GitHub (Jun 12, 2024):
Did not had the time yet to test. It does not crash and properly answers when I use the model via curl. I noticed this line in the logs:
The ollama server is started with
runners/cpu_avx2, obviously CPU only. Here is the full log:It tries to load to GPU, fails, and falls back to CPU
@5310 commented on GitHub (Jun 12, 2024):
So, I ran this again:
llama3:8bon the Deck with Docker (well, Podman since SteamOS now has it preinstalled) with debug on.I wasn't paying enough attention, but I also get the line about ROCm, and it should be 1GB for the Deck by default.
Only I realized at this point my VRAM had reset back to 1GB again from the 4GB I had it set to before. Neither
llama3:8bnorgemma:2bwould probably run on it anyway. While I reboot to increase my VRAM allocation again, here's my run info—System information:
Ollama log:
Edit: Increased the VRAM to 4GB. Ollama log reflect the change, but trying to run anything throws
Could not initialize Tensile host: No devices found. Unlike before, at 1GB VRAM, it doesn't even run on the CPU. I can only run it on the CPU by setting invalidHIP_VISIBLE_DEVICES.@sebastianlutter commented on GitHub (Jun 13, 2024):
I'll wait until SteamOS 3.6 is released, I'm pretty sure it will work then. I failed with some attempts to build the current ollama in a
rocm/dev-ubuntu-22.04:5.4.2docker container.Btw: I was able to run Llama3 8B on GPU using mlc.ai and vulkan:
I like the idea of using vulkan to access the GPU because this will also work with Intel GPUs. But I expect rocm to have better performance (and I really hate the need to use anaconda to get it working)
@dhiltgen commented on GitHub (Jun 19, 2024):
Release 0.1.45 will have a ROCm version bump to v6.1.1 which might help compatibility between ROCm and the driver.
@Talleyrand-34 commented on GitHub (Jun 26, 2024):
Sorry if this is not ollama area but when will this new steamos update allow to have ollama rocm?
Now it is going out SteamOS 3.6.7, so in which version of steamos we can expect ollama 0.1.45
@sebastianlutter commented on GitHub (Jul 3, 2024):
@Talleyrand-34 The current stable Steam OS is 3.5.x, currently 3.6.7 is in preview, 3.6.6 is in beta. When 3.6.x gets stable and shipped to normal users then most probably the current llama build will work. The 3.5.x has a too old kernel and rocm driver for current ollama to work. The updated rocm version in 3.6.x should do the trick. But this is guessing, not science ;)
@luckydonald commented on GitHub (Jul 18, 2024):
With podman being installed per default (as claimed above), would it make sense to adapt the install script to handle installing on steam deck via podman?
All it currently does is complain about /usr/local/bin/ollama being a read only file system.
@dhiltgen commented on GitHub (Jul 22, 2024):
@luckydonald there's already an official ollama rocm container image
ollama/ollama:rocm- see https://hub.docker.com/r/ollama/ollama@Mushoz commented on GitHub (Oct 25, 2024):
SteamOS 3.6 is now in stable with the newer kernel. Any updates on this ticket? Does it work properly now?
@sebastianlutter commented on GitHub (Oct 26, 2024):
https://www.gamingonlinux.com/2024/10/steam-deck-steamos-36-officially-out-with-improved-performance-mura-compensation-lots-more/
Hope I can find time to run a test the next days
@sebastianlutter commented on GitHub (Oct 26, 2024):
First test:
The gpu was found and it tried to use it, but had too less memory available to put any layer to the GPU memory. But promising so far . . .
Time to give the GPU more memory I guess: https://pimylifeup.com/steam-deck-bios/
To inspect the gpu usage I found
nvtop(installable via pacman) very handy@sebastianlutter commented on GitHub (Oct 26, 2024):
I increased the GPU memory to 4GB, then tested again with llama3.2:1b
@7h145 commented on GitHub (Oct 27, 2024):
Can confirm "won't work" on Steam Deck, SteamOS 3.6.19 in "desktop mode", running podman in rootless mode with either of
My logs below are from ollama:0.4.0-rc5-rocm.
The exact mode of "won't work" is different for
HSA_OVERRIDE_GFX_VERSION=10.3.0vsHSA_OVERRIDE_GFX_VERSION=gfx1030; the ollama server does run at first with either one (see below), but both fail on inference: while10.3.0does load the model very slowly and fails afterwards,gfx1030fails immediately withCould not initialize Tensile host.In both cases the ollama server starts up "more or less fine":
HSA_OVERRIDE_GFX_VERSION=10.3.0HSA_OVERRIDE_GFX_VERSION=gfx1030The diff (without timestamp differences) is...
As in "nothing to see here"? Maybe this "loads more or less fine" is what people reported as success earlier?
But on actual inference (e.g.
podman exec -it ollama ollama run llama3.2:1b), these two variants behave indeed differently:The
HSA_OVERRIDE_GFX_VERSION=10.3.0does find the device and loads the model, but does so very, very slowly, then hangs (indefinitely?)This seems to be a memory allocation thing; the actual slowness of the loading seems to differ depending on previously allocated UMA frame buffer "VRAM". The example above is on "cold" VRAM, taking 30 minutes for an 1b model.
But after all this tedious loading, the inference just hangs indefinitely with
The
HSA_OVERRIDE_GFX_VERSION=gfx1030fails immediatelyThis error has been reported previously; it appears to me that
gfx1030is not helpful here and the documentation indicates that this is not even a recognized value forHSA_OVERRIDE_GFX_VERSION. I'm pretty sure that this is not apodmanpermission issue as speculated above (at least in my case).I can provide more logs, but this gets byzantine fast, especially with
AMD_LOG_LEVEL=3.It seems to me that this is an incompatibility between current ROCm and the "AMD Custom APU 0405" in the Steam Deck?
Ps: Suggestion for easier debugging: maybe include
rocminfoandrocm-smiin theollama:rocmimages?@7h145 commented on GitHub (Oct 27, 2024):
Addendum ... Logs with
OLLAMA_DEBUG=1andAMD_LOG_LEVEL=3.Same setup as before: Steam Deck, SteamOS 3.6.19 in "desktop mode", podman rootless. Using only
HSA_OVERRIDE_GFX_VERSION=10.3.0here.Running ollama (at 2024-10-27T12:51:19) with
and then running inference (at 2024-10-27T12:51:26) with
yields the following rather lengthy (300kb) log; the llama3.2:1b model needs about 55 minutes to load, the inference hangs indefinitely after that.
The server startup is complete at 2024-10-27T12:51:19
The inference starts at 2024-10-27T12:51:26
The model is successfully loaded at 2024-10-27T13:47:01 after about 55 Minutes
At this point, the inference just hangs/does "nothing".
Stopping the inference via
^Cat 2024-10-27T13:51:50 yieldsRemark: Kind of a toy problem as long as the "VRAM" on the Deck is limited to 4g (and ultra-slow). This is all somewhat interesting and "should work" IMHO, but the real world use cases for something like this are limited. The up to 4g UMA frame buffer "VRAM" the Steam Deck APU provides can offload only small models which will in most cases run more or less acceptable on the Steam Deck CPU.
@ehartford commented on GitHub (Nov 8, 2024):
Anyone had success with this?
@Talleyrand-34 commented on GitHub (Nov 15, 2024):
In my case the rocm docker container with podman (you can use docker)
@sebastianlutter commented on GitHub (Nov 18, 2024):
Have had no success with ollama docker yet, and lacking time for further tests